Grand challenges in interfacing engineering with life sciences and medicine

Toward Blood-Based Precision Medicine: Identifying Age-Sex-Specific Vascular Biomarker Quantities on Circulating Vascular Cells

Introduction

Abnormal angiogenesis is central to vascular disease and cancer, and noninvasive biomarkers of vascular origin are needed to evaluate patients and therapies. Vascular endothelial growth factor receptors (VEGFRs) are often dysregulated in these diseases, making them promising biomarkers, but the need for an invasive biopsy has limited biomarker research on VEGFRs. Here, we pioneer a blood biopsy approach to quantify VEGFR plasma membrane localization on two circulating vascular proxies: circulating endothelial cells (cECs) and circulating progenitor cells (cPCs).

Methods

Using quantitative flow cytometry, we examined VEGFR expression on cECs and cPCs in four age-sex groups: peri/premenopausal females (aged < 50 years), menopausal/postmenopausal females (≥ 50 years), and younger and older males with the same age cut-off (50 years).

Results

cECs in peri/premenopausal females consisted of two VEGFR populations: VEGFR-low (~ 55% of population: population medians ~ 3000 VEGFR1 and 3000 VEGFR2/cell) and VEGFR-high (~ 45%: 138,000 VEGFR1 and 39,000-236,000 VEGFR2/cell), while the menopausal/postmenopausal group only possessed the VEGFR-low cEC population; and 27% of cECs in males exhibited high plasma membrane VEGFR expression (206,000 VEGFR1 and 155,000 VEGFR2/cell). The absence of VEGFR-high cEC subpopulations in menopausal/postmenopausal females suggests that their high-VEGFR cECs are associated with menstruation and could be noninvasive proxies for studying the intersection of age-sex in angiogenesis. VEGFR1 plasma membrane localization in cPCs was detected only in menopausal/postmenopausal females, suggesting a menopause-specific regenerative mechanism.

Conclusions

Overall, our quantitative, noninvasive approach targeting cECs and cPCs has provided the first insights into how sex and age influence VEGFR plasma membrane localization in vascular cells.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12195-023-00771-1.

Pain Influences Neuropsychological Performance Following Electrical Injury: A Cross-Sectional Study

OBJECTIVE

Electrical injury (EI) is a significant, multifaceted trauma often with multi-domain cognitive sequelae, even when the expected current path does not pass through the brain. Chronic pain (CP) research suggests pain may affect cognition directly and indirectly by influencing emotional distress which then impacts cognitive functioning. As chronic pain may be critical to understanding EI-related cognitive difficulties, the aims of the current study were: examine the direct and indirect effects of pain on cognition following EI and compare the relationship between pain and cognition in EI and CP populations.

METHOD

This cross-sectional study used data from a clinical sample of 50 patients with EI (84.0% male; M_age = 43.7 years) administered standardized measures of pain (Pain Patient Profile), depression, and neurocognitive functioning. A CP comparison sample of 93 patients was also included.

RESULTS

Higher pain levels were associated with poorer attention/processing speed and executive functioning performance among patients with EI. Depression was significantly correlated with pain and mediated the relationship between pain and attention/processing speed in patients with EI. When comparing the patients with EI and CP, the relationship between pain and cognition was similar for both clinical groups.

CONCLUSIONS

Findings indicate that pain impacts mood and cognition in patients with EI, and the influence of pain and its effect on cognition should be considered in the assessment and treatment of patients who have experienced an electrical injury.

Numerical investigation of different viscosity models on pulsatile blood flow of thoracic aortic aneurysm (TAA) in a patient-specific model

Aortic aneurysm is one of the most common aortic diseases that can lead to unfortunate consequences. Numerical simulations have an important role in the prediction of the aftereffects of vascular diseases including aneurysm. In this research, numerical simulation of pulsatile blood flow is performed for a 3-dimensional patient-specific model of a thoracic aortic aneurysm (TAA). Since the choice of blood viscosity model may have a significant impact on the simulation results, the effects of four non-Newtonian models of blood viscosity namely Carreau, Casson, Herschel-Bulkley, power low, and the Newtonian model on the wall shear stress (WSS) distribution, shear rate, and oscillatory shear index (OSI) have been analyzed. Simulation results showed that all the non-Newtonian and Newtonian models generally, predict similar patterns for blood flow and shear rate. At high flow rates in the cardiac cycle, the WSS value for all the models are similar to each other except for the power-law model due to the shear thinning behavior. All models predict high values of OSI on the inner wall of the ascending aorta and broad areas of the inner wall of the aneurysm sac. However, the Newtonian model predicts the OSI less than the non-Newtonian models in some areas of the aneurysm sac. Results indicated that the Newtonian model generally can predict the hemodynamic parameters of the blood flow similar to the non-Newtonian but for more precise analysis and to predict the regions prone to rupture and atherosclerosis, choosing a proper non-Newtonian model is recommended.

General guidelines for biomedical software development

Most bioinformatics tools available today were not written by professional software developers, but by people that wanted to solve their own problems, using computational solutions and spending the minimum time and effort possible, since these were just the means to an end. Consequently, a vast number of software applications are currently available, hindering the task of identifying the utility and quality of each. At the same time, this situation has hindered regular adoption of these tools in clinical practice. Typically, they are not sufficiently developed to be used by most clinical researchers and practitioners. To address these issues, it is necessary to re-think how biomedical applications are built and adopt new strategies that ensure quality, efficiency, robustness, correctness and reusability of software components. We also need to engage end-users during the development process to ensure that applications fit their needs. In this review, we present a set of guidelines to support biomedical software development, with an explanation of how they can be implemented and what kind of open-source tools can be used for each specific topic.

General guidelines for biomedical software development

Most bioinformatics tools available today were not written by professional software developers, but by people that wanted to solve their own problems, using computational solutions and spending the minimum time and effort possible, since these were just the means to an end. Consequently, a vast number of software applications are currently available, hindering the task of identifying the utility and quality of each. At the same time, this situation has hindered regular adoption of these tools in clinical practice. Typically, they are not sufficiently developed to be used by most clinical researchers and practitioners. To address these issues, it is necessary to re-think how biomedical applications are built and adopt new strategies that ensure quality, efficiency, robustness, correctness and reusability of software components. We also need to engage end-users during the development process to ensure that applications fit their needs. In this review, we present a set of guidelines to support biomedical software development, with an explanation of how they can be implemented and what kind of open-source tools can be used for each specific topic.

Fabrication of 3D Biomimetic Microfluidic Networks in Hydrogels

A laser-based hydrogel degradation technique is developed that allows for local control over hydrogel porosity, fabrication of 3D vascular-derived, biomimetic, hydrogel-embedded microfluidic networks, and generation of two intertwining, yet independent, microfluidic networks in a single construct.

New Perspectives on Neuroengineering and Neurotechnologies: NSF-DFG Workshop Report

GOAL

To identify and overcome barriers to creating new neurotechnologies capable of restoring both motor and sensory function in individuals with neurological conditions.

METHODS

This report builds upon the outcomes of a joint workshop between the US National Science Foundation and the German Research Foundation on New Perspectives in Neuroengineering and Neurotechnology convened in Arlington, VA, USA, November 13-14, 2014.

RESULTS

The participants identified key technological challenges for recording and manipulating neural activity, decoding, and interpreting brain data in the presence of plasticity, and early considerations of ethical and social issues pertinent to the adoption of neurotechnologies.

CONCLUSIONS

The envisaged progress in neuroengineering requires tightly integrated hardware and signal processing efforts, advances in understanding of physiological adaptations to closed-loop interactions with neural devices, and an open dialog with stakeholders and potential end-users of neurotechnology.

SIGNIFICANCE

The development of new neurotechnologies (e.g., bidirectional brain-computer interfaces) could significantly improve the quality of life of people living with the effects of brain or spinal cord injury, or other neurodegenerative diseases. Focused efforts aimed at overcoming the remaining barriers at the electrode tissue interface, developing implantable hardware with on-board computation, and refining stimulation methods to precisely activate neural tissue will advance both our understanding of brain function and our ability to treat currently intractable disorders of the nervous system.

Magneto acoustic tomography with short pulsed magnetic field for in-vivo imaging of magnetic iron oxide nanoparticles

Nanoparticles are widely used as contrast and therapeutic agents. As such, imaging modalities that can accurately estimate their distribution in-vivo are actively sought. We present here our method Magneto Acoustic Tomography (MAT), which uses magnetomotive force due to a short pulsed magnetic field to induce ultrasound in the magnetic nanoparticle labeled tissue and estimates an image of the distribution of the nanoparticles in-vivo with ultrasound imaging resolution. In this study, we image the distribution of superparamagnetic iron oxide nanoparticles (IONP) using MAT method. In-vivo imaging was performed on live, nude mice with IONP injected into LNCaP tumors grown subcutaneously within the hind limb of the mice. Our experimental results indicate that the MAT method is capable of imaging the distribution of IONPs in-vivo. Therefore, MAT could become an imaging modality for high resolution reconstruction of MNP distribution in the body.

FROM THE CLINICAL EDITOR

Many magnetic nanoparticles (MNPs) have been used as contrast agents in magnetic resonance imaging. In this study, the authors investigated the use of ultrasound to detect the presence of MNPs by magneto acoustic tomography. In-vivo experiments confirmed the imaging quality of this new approach, which hopefully would provide an alternative method for accurate tumor detection.

Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms

Brain-computer interfaces (BCIs) have been explored in the field of neuroengineering to investigate how the brain can use these systems to control external devices. We review the principles and approaches we have taken to develop a sensorimotor rhythm EEG based brain-computer interface (BCI). The methods include developing BCI systems incorporating the control of physical devices to increase user engagement, improving BCI systems by inversely mapping scalp-recorded EEG signals to the cortical source domain, integrating BCI with noninvasive neuromodulation strategies to improve learning, and incorporating mind-body awareness training to enhance BCI learning and performance. The challenges and merits of these strategies are discussed, together with recent findings. Our work indicates that the sensorimotor-rhythm-based noninvasive BCI has the potential to provide communication and control capabilities as an alternative to physiological motor pathways.

Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health.

A brief history of tissue models for cardiac electrophysiology

The last four decades have produced a number of significant advances in the developments of computer models to simulate and investigate the electrical activity of cardiac tissue. The tissue descriptions that underlie these simulations have been built from a combination of clever insight and careful comparison with measured data at multiple scales. Tissue models have not only led to greater insights into the mechanisms of life-threatening arrhythmias but have been used to engineer new therapies to treat the consequences of cardiac disease. This paper is a look back at the early years in the cardiac modeling and the challenges facing the field as models move toward the clinic.

The impact of mind-body awareness training on the early learning of a brain-computer interface

Brain-computer interface (BCI) systems allow users to interact with their environment by bypassing muscular control to tap directly into the users' thoughts. In the present study, we investigate the role of prior experience with yoga and meditation, examples of formalized mind-body awareness training (MBAT), in learning to use a one-dimensional sensorimotor rhythm based BCI. Thirty-six human subjects volunteered to participate in two different cohorts based on past experience with MBAT - experienced MBAT practitioners and controls. All subjects participated in three BCI experiments to achieve competency in controlling the BCI system. The MBAT cohort achieved BCI competency significantly faster than the control cohort. In addition, the MBAT cohort demonstrated enhanced ability to control the system on various measures of BCI performance and improved significantly more over time when compared to control. Our work provides insight into valuable strategies for reducing barriers to BCI fluency that limit the more widespread use of these systems.

The Business Engineering Surgical Technologies (BEST) teaching method: incubating talents for surgical innovation

INTRODUCTION

Technological innovation in surgical science and healthcare is vital and calls for close collaboration between engineering and surgery. To meet this objective, BEST was designed as a free sustainable innovative teaching method for young professionals, combining surgery, engineering, and business in a multidisciplinary, high-quality, low-cost, and learning-by-doing philosophy.

AIMS

This paper reviews the initial outcomes of the program and discusses lessons learned and future directions of this innovative educational method.

METHODS

BEST educational method is delivered in two parts: the first component consisting of live streaming or pre-recorded online lectures, with an interdisciplinary profile focused on surgery, engineering, and business. The second component is an annual 5-day on-site course, organized at IRCAD-IHU, France. The program includes workshops in engineering, entrepreneurship team projects, and in-depth hands-on experience in laparoscopy, robotic surgery, interventional radiology, and flexible endoscopy with special emphasis on the interdisciplinary aspect of the training. A panel of surgeons, engineers, well-established entrepreneurs, and scientists assessed the team projects for potential patent application.

RESULTS

From November 2011 till September 2013, 803 individual and institutional users from 79 different countries attended the online course. In total, 134 young professionals from 32 different countries applied to the onsite course. Sixty participants were selected each year for the onsite course. In addition, five participants were selected for a web-based team. Thirteen provisional patents were filed for the most promising projects.

CONCLUSION

BEST proved to be a global talent incubator connecting students to high-quality education despite institutional and economical boundaries. Viable and innovative ideas arose from this revolutionary approach which is likely to spin-off significant technology transfer and lead the way for future interdisciplinary hybrid surgical education programs and career paths.

Quantitative characterization of cellular membrane-receptor heterogeneity through statistical and computational modeling

Cell population heterogeneity can affect cellular response and is a major factor in drug resistance. However, there are few techniques available to represent and explore how heterogeneity is linked to population response. Recent high-throughput genomic, proteomic, and cellomic approaches offer opportunities for profiling heterogeneity on several scales. We have recently examined heterogeneity in vascular endothelial growth factor receptor (VEGFR) membrane localization in endothelial cells. We and others processed the heterogeneous data through ensemble averaging and integrated the data into computational models of anti-angiogenic drug effects in breast cancer. Here we show that additional modeling insight can be gained when cellular heterogeneity is considered. We present comprehensive statistical and computational methods for analyzing cellomic data sets and integrating them into deterministic models. We present a novel method for optimizing the fit of statistical distributions to heterogeneous data sets to preserve important data and exclude outliers. We compare methods of representing heterogeneous data and show methodology can affect model predictions up to 3.9-fold. We find that VEGF levels, a target for tuning angiogenesis, are more sensitive to VEGFR1 cell surface levels than VEGFR2; updating VEGFR1 levels in the tumor model gave a 64% change in free VEGF levels in the blood compartment, whereas updating VEGFR2 levels gave a 17% change. Furthermore, we find that subpopulations of tumor cells and tumor endothelial cells (tEC) expressing high levels of VEGFR (>35,000 VEGFR/cell) negate anti-VEGF treatments. We show that lowering the VEGFR membrane insertion rate for these subpopulations recovers the anti-angiogenic effect of anti-VEGF treatment, revealing new treatment targets for specific tumor cell subpopulations. This novel method of characterizing heterogeneous distributions shows for the first time how different representations of the same data set lead to different predictions of drug efficacy.

Quantitative fluorescent profiling of VEGFRs reveals tumor cell and endothelial cell heterogeneity in breast cancer xenografts

Plasma membrane-localized vascular endothelial growth factor receptors (VEGFR) play a critical role in transducing VEGF signaling toward pro and antiangiogenic outcomes and quantitative characterization of these receptors is critical toward identifying biomarkers for antiangiogenic therapies, understanding mechanisms of action of antiangiogenic drugs, and advancing predictive computational models. While in vitro analysis of cell surface-VEGFRs has been performed, little is known about the levels of cell surface-VEGFR on tumor cells. Therefore, we inoculate nude mice with the human triple-negative breast cancer, MDA-MB-231, cell line; isolate human tumor cells and mouse tumor endothelial cells from xenografts; and quantitatively characterize the VEGFR localization on these cells. We observe 15,000 surface-VEGFR1/tumor endothelial cell versus 8200 surface-VEGFR1/tumor endothelial cell at 3 and 6 weeks of tumor growth, respectively; and we quantify 1200-1700 surface-VEGFR2/tumor endothelial cell. The tumor cell levels of VEGFR1 and VEGFR2 are relatively constant between 3 and 6 weeks: 2000-2200 surface-VEGFR1/tumor cell and ~1000 surface-VEGFR2/tumor cell. Cell-by-cell analysis provides additional insight into tumor heterogeneity by identifying four cellular subpopulations based on size and levels of cell membrane-localized VEGFR. Furthermore, when these ex vivo data are compared to in vitro data, we observe little to no VEGFRs on MDA-MB-231 cells, and the MDA-MB-231 VEGFR surface levels are not regulated by a saturating dose of VEGF. Overall, the quantification of these dissimilarities for the first time in tumor provides insight into the balance of modulatory (VEGFR1) and proangiogenic (VEGFR2) receptors.

Medical and biological engineering in the next 20 years: the promise and the challenges

In 2011, the American Institute for Medical and Biological Engineering (AIMBE) (www.aimbe.org) celebrated its 20th anniversary by undertaking to identify major societal challenges to which medical and biological engineers can contribute solutions in the next 20 years. This report is a summary of the six major challenges that were identified. The report also discusses some specific areas within these high-level challenges that can form the basis for policy action, provides a brief rationale for pursuing those areas, and discusses roadblocks to progress. The six overarching challenges are: 1) engineering safe and sustainable water and food supply, 2) engineering personalized health care, 3) engineering solutions to injury and chronic diseases, 4) engineering global health through infectious disease prevention and therapy, 5) engineering sustainable bioenergy production, and 6) engineering the 21st century US economy. While arrived at independently by AIMBE, many of the elements overlap with similar challenges identified by other bodies. The similarities highlight the central mission of medical and biological engineers, working with other experts, which is to solve important problems central to human health and welfare.